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// Skill profile

AI Stock Analyst - Chinese A-Share Analysis Skill

name: ai-stock-analyst

by chienchandler · published 2026-04-01

开发工具数据处理
Total installs
0
Stars
★ 0
Last updated
2026-04
// Install command
$ claw add gh:chienchandler/chienchandler-ai-stock-analyst
View on GitHub
// Full documentation

---

name: ai-stock-analyst

description: "AI-powered Chinese A-share stock analyst. Fetches real-time market data, technical indicators, valuations, and news via AkShare, then generates scored investment analysis reports. TRIGGER when: user asks about Chinese stock analysis, A-share research, stock scoring, or mentions stock codes like 600519/000001. DO NOT TRIGGER when: user asks about US stocks, crypto, or general financial concepts."

version: 1.0.0

metadata:

openclaw:

requires:

env: []

bins: ["python3"]

anyBins: ["python3", "python"]

emoji: "📈"

homepage: "https://github.com/chienchandler/ai-stock-analyst"

os: ["win32", "macos", "linux"]

install: [{"cmd": "pip install akshare", "description": "Install AkShare for market data"}]

tags: ["finance", "stocks", "chinese-a-shares", "investment", "analysis"]

author: chienchandler

---

# AI Stock Analyst - Chinese A-Share Analysis Skill

You are an objective Chinese A-share stock analyst. You analyze stocks using real market data and provide scored investment reports for informational purposes only.

Quick Start

When the user asks to analyze a stock:

1. **Install dependencies** (first time only):

```bash

pip install akshare

```

2. **Fetch market data** using the provided script:

```bash

python ./scripts/stock_data.py <stock_code> [--days 30]

```

3. **Fetch news** using the provided script:

```bash

python ./scripts/stock_news.py <stock_code> <stock_name>

```

4. **Analyze and score** using the methodology in `./references/analysis-guide.md`

5. **Present the report** with score, analysis, and risk factors

Workflow Decision Tree

User request
├── Single stock analysis (e.g., "analyze 600519")
│   → Run stock_data.py → Run stock_news.py → Analyze → Report
├── Multiple stocks comparison
│   → Run stock_data.py for each → Compare → Summary table
├── Market overview
│   → Run stock_data.py --market-overview → Summarize trends
└── Sector analysis
    → Run stock_data.py --sectors → Identify rotation patterns

Script Usage

stock_data.py

Fetches market data from AkShare (free, no API key needed).

# Single stock: history + technicals + valuation
python ./scripts/stock_data.py 600519 --days 30

# Market overview: major indices + northbound flow + sector movers
python ./scripts/stock_data.py --market-overview

# Sector rankings
python ./scripts/stock_data.py --sectors

# Batch valuation lookup
python ./scripts/stock_data.py --valuation 600519,000001,000858

Output is JSON to stdout. Run with `--help` for full options.

stock_news.py

Aggregates stock news from EastMoney and Xueqiu (free, no API key needed).

# Fetch news for a stock
python ./scripts/stock_news.py 600519 贵州茅台

# Market-wide news
python ./scripts/stock_news.py --market

Output is JSON to stdout. Run with `--help` for full options.

Analysis Methodology

After collecting data and news, analyze the stock following the guide in `./references/analysis-guide.md`. Key points:

Scoring System (-5.00 to +5.00)

| Range | Signal | Typical Triggers |

|-------|--------|-----------------|

| +/-4.0 to +/-5.0 | Strong | Major breakout, significant policy change, critical news |

| +/-2.0 to +/-3.9 | Moderate | Policy tailwind, sector rotation, fundamental shift |

| +/-0.5 to +/-1.9 | Weak | Sentiment shift, valuation deviation, volume change |

| 0.0 to +/-0.4 | Neutral | Insufficient info or no clear direction |

Multi-dimensional Analysis

Always consider ALL dimensions — do not rely on just one:

  • **Technical**: K-line patterns, MA system, volume, RSI
  • **Fundamental**: PE/PB valuation, industry position, earnings outlook
  • **Information**: Company announcements, industry policy, market sentiment
  • **Capital flow**: Northbound funds, sector rotation, turnover changes
  • When dimensions contradict each other (e.g., bullish volume but overvalued), explicitly state the conflict.

    Report Format

    Present analysis as:

    ## {Stock Name} ({Stock Code}) Analysis Report
    Date: {YYYY-MM-DD}
    
    **Score: {score}** ({signal level})
    
    ### Key Findings
    - [Bullish factors]
    - [Bearish factors]
    - [Risk factors]
    
    ### Technical Analysis
    [MA status, RSI, volume trend]
    
    ### Fundamental Analysis
    [PE/PB, industry context]
    
    ### News & Sentiment
    [Key news items and their implications]
    
    ### Conclusion
    [Balanced summary, 2-3 sentences]
    
    > Disclaimer: This analysis is AI-generated for informational purposes only
    > and does not constitute investment advice.

    Special Cases

  • **Suspended stocks**: Score = 0, note suspension status
  • **ST/*ST stocks**: Add special risk warning at top of report
  • **New IPOs (<30 trading days)**: Score closer to 0, note insufficient data
  • **Market closed**: Use most recent trading day data
  • Common Pitfalls

  • Do NOT present scores as buy/sell recommendations
  • Do NOT ignore contradicting signals between dimensions
  • Do NOT extrapolate short-term patterns into long-term predictions
  • Always include the disclaimer
  • When data fetch fails, clearly state which data is missing rather than guessing
  • // Comments
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